Summary: Analysed results of a new player test in Playscan show that “The Dream of Winning the Jackpot” is the biggest motivation for gambling – which seems to also be the one category of motivation that also holds the smallest proportion of at-risk players. The player type “The Thrill Seeker” holds the largest proportion of at-risk gamblers.
For gaming companies, including responsible gambling departments, the question of why people gamble is both important and interesting. Most gamblers lose and gambling could sometimes appear a bit irrational, as an activity. But still, people like to gamble. What is it about gambling that attracts so strongly? What motivates people to gamble?
Motives for gambling
For some people, the dream of winning millions on the lottery is the biggest motive for gambling. Those who seek intellectual stimulation prefer games where skill is considered to be important, such as horse betting and poker. Professor Per Binde, gambling researcher at the University of Gothenburg, has studied motives for gambling. He describes five underlying motives: the dream of hitting the jackpot, social rewards, intellectual challenge, mood change and what he describes as the core and most characteristic motive when it comes to gambling – the chance of winning.
Are you a team player – or a fortune hunter?
With Binde’s research in mind, we teamed up with phycologists from Sustainable Interaction and created a self-assessment test and launched it inside Playscan to help players understand and reflect upon their own motives for gambling, what player type they are – and risks associated with them.
The test consists of seven questions. Based on their answers, preferred games (chance-based or skill-based games) and motives for gambling the player is assigned a “player type” – with customized recommendations to that specific player type. We created ten different types:
The typical test-taker is a 45-year-old man
We analysed data from 2 000 tests and found that the test had an above sufficient completion rate of nearly 80 %. Unsurprisingly, more men than females took the test, 84 % male versus 16 % female test-takers. Worth noting is that Playscan in general get more visitors from at-risk players – and a large porportion of those are men.
The most common player type was found to be the “The Dreamer”, followed by “The Hard Earner” and “The Expert”.
The dream of winning the jackpot was by far the biggest motivation, followed by earning money, and the intellectual challenge.
How do the different motives relate to at-risk gambling?
If we study the proportion of at-risk players in each motivational category – we’ll see that the Jackpot motivation holds 20% fewer at-risk gamblers than the full sample. The motives “gambling as a way to earn money” and “as an intellectual challenge” seem to attract a larger proportion of at-risk players, however these relations are not statistically significant.
What player types are more problematic?
The player types that stand out with a higher proportion of at-risk players are ”The Hard Earner” and ”The Thrill seeker”. “The Dreamer”, “The Fortune Hunter” and “The Escapist” contain fewer at-risk players. For the other player types the relations are not statistically significant.
Do you want to know more about this test? Or Playscan? Contact us!
With a strong strategy for consumer protection the Norwegian gaming company Norsk Tipping has dedicated much effort in providing attractive gambling – within a responsible setting.
The company has been a client of Playscan since 2014 and are now signing a new agreement for partnership, with the continuing right to use Playscan as their Responsible Gaming Tool (RGT). The agreement will last up to six years.
– The tool and the risk analysis plays a key role in our work to prevent problem gambling. We are very pleased to continue the collaboration with Svenska Spels Playscan, says Bjørn Helge Hoffmann, Responsible Gaming Manager at Norsk Tipping
– It is important for Norsk Tipping to work with a tool that is based on science and knowledge on problem gambling, which we put much effort in. With their commitment to raise the bar for responsible gambling even higher, Norsk Tipping is a very important partner to us, says Annika Hjälm, Head of Playscan, Svenska Spel.
We know from previous research that emotions and feelings play a central part in problem gambling. We also know that emotions tend to influence our decisions and affect risk attitudes when gambling. But can we, by creating a self-assessment test with personal feedback, increase the player’s knowledge on how emotions affect their ability to make rational decisions when gambling?
The answer is: Yes, partly.
10 000 tests were analysed
When we studied the test-answers and compared them to the player’s Playscan score (low, medium or high-risk player), we saw that low risk and medium risk players increased their knowledge about the role of emotions. However, the main finding was that moderate risk and problem gamblers tend to be influenced by their emotional state to a much higher degree, and that they themselves were aware of this behaviour.
Creating a self-assessment test
We have learnt that people like taking self-assessment tests – especially if they can tell you more about yourself. How smart you appear to be, what you apparently like to do and what type of personality you appear to have.
With this in mind, we created a test and named it “Who decides?”. The test-taker is asked a series of questions to decide if they are playing mostly while under rational, or emotional influence – hot or cold cognition.
Hot cognition is a hypothesis on cognition affected by emotion, while decision making with cold cognition is more likely to involve logic and critical analysis.
The test took about three minutes to finish and was offered to players who had activated Playscan. The players answered questions like: “To what extent does your feelings affect you when gambling” and “Do you find it easy to stop gambling when you are winning/losing”? We also wrote some scenarios in which the player had to take a stand:
“Imagine that you have gambled for a while and won a total of 800 SEK. Do you continue gambling, or are you satisfied with your prize and do you stop gambling that moment?”
After the test the players got feedback, mirroring their answers, for example, “Your answers show that you seem to have a hard time stopping your gambling when winning.”
Our underlying assumption was challenged
We assumed that players have a poor understanding of how emotions or being in a state of hot or cold cognition, affect their decisions while gambling. Our result shows that most players actually understand that their emotions affect their ability to stop gambling. Can this information be useful for future responsible gambling initiatives or even research?
We believe that there is a lot of opportunity in responsible gambling from studying player’s perception of their gambling behaviour. With these findings in mind, we are now developing a new test, to better target the state of high-risk players –with the goal of nudging them into making smart decisions when gambling.
In April this year the Playscan team attended the Discovery conference, hosted by the Responsible Gambling Council in Toronto, and spoke about the responsible gambling approach of the Swedish state lottery, Svenska Spel.
In short, this is what we argued:
Registered play can help us act
The collection, storage and analysis of player data has made it possible for Svenska Spel to create a responsible gambling framework that is both personalised and measurable. The framework sets out from the player’s gambling behaviour – and if that behaviour is excessively risky, he or she is notified. The player is offered tools to help them gain control, such as a consumption history view, limit setting and self-exclusion. The success of these efforts, from identifying problem gambling to seeking contact and how well these tools are used by players, can all be measured and appropriate KPIs can be set.
Things Svenska Spel actively avoid, for responsible gambling
Based on what we know drives problematic gambling Svenska Spel does not offer any bonuses or loyalty programmes. Elevated risk games are marketed restrictively and there is no marketing aimed at high risk players. This is important to recognise: an effective responsible gambling framework is not only about educating players on how to play smart – it is also about, from an operator’s perspective, acknowledging that responsible gambling means saying no to profits coming from high risk players.
Do you want to meet us? We’ll be at the EASG conference, in Malta, 11-14 September 2018. Contact us and we’ll gladly tell you more about our work!
During four weeks in November 2017, we contacted around 70 high-risk players by telephone, informing them about their gambling habits at Svenska Spel. We found that players have a poor understanding of how much money they spend – and they appreciate the information.
Why contacting players by telephone?
One responsibility for gambling companies is to minimise the risk for their players to develop gambling problems. We know a whole about the negative consequences that affect the individual and his/her closest near and dear, and the consequences are devastating. They affect all parts of the individual’s life, economically, socially, and psychologically.
We believe that transparency, showing how much gambling really costs, would lead to better-informed consumers. By contacting at-risk players, we wanted to investigate if conversations by phone was an appreciated service and if it could prevent and reduce any adverse consequences from gambling.
The idea of giving at-risk players feedback by telephone is not new to Svenska Spel. The Norwegian gambling company Norsk Tipping started as early as 2014 and has now a permanent organisation for this type of proactive calls.
The content of the conversations
The pilot had an exploratory design in which we concentrated on the players’ reaction to the call. In the first phase, the project group was trained by a physiologist in different conversational techniques and developed a conversation concept. The conversations aimed to make the player more aware of his or hers gambling consumption, inviting them to reflect upon their habits. If the player was interested, we offered information about possible action for increased control, guiding them to appropriate help and treatment options.
Which customers did we contact?
For this pilot we used information from the Playscan system and selected three target groups to contact:
Big losers: a high-risk profile in Playscan and lost (net loss) more than 800 euro the last month.
Young risk players: men, 18-25 years, a high-risk profile in Playscan and lost (net loss) more than 400 euro the previous month.
Problematic gambling profile: We call this group because they, through the self-test, have told us they have problems with their gambling.
How did they respond?
Prior our first call we were naturally a bit nervous. How would the player react? How do we handle if someone gets sad? Or angry? There were many questions before our first call, but very soon we were strengthened by the fact that several expressed their gratitude and we were convinced that we have a good reason to call these customers. Some conversations did not lead to any concrete actions, such as changing someone’s limits or even helping someone to take a break from gambling, but the conversation seemed to be appreciated. Some said that they can afford to play as they do, but that “it’s good that we are calling”.
Five weeks after the intervention, we see that contacted customers spend less money on gambling (both net and gross) compared to customers we tried to contact but didn’t answer. However, the result is not statistically significant. The average length of the conversation was 7 minutes, and the average age of the customer was 37 years old. Out of the 71 phone calls 11 people chose some type self-exclusion immediately at the time of the call. The most common conversation, however, concerned limit setting and information about the consumption history view. At the end of each call, the customer was asked if they appreciated the conversation. 98% was either positive or neutral towards the call.
The project had a positive impact internally at Svenska Spel. Staff, throughout the entire organisation, were very supportive towards the project. And also, when communicating it externally, it created good PR for the company.
The intervention is still being evaluated with follow up questionnaires to contacted customers. However, since the early results indicate a positive effect on player behaviour, we plan to continue the conversations – especially since the customers seem to appreciate the service.
In the thesis “The use and experience of responsible gambling tools: An explorative analysis of user behaviour regarding a responsible gambling tool and the consequences of use” David Forsström explores different aspects of the use, experience and functions of Playscan. The thesis shows that Playscan is most commonly used by players with a higher risk level, the self-test is the most used feature and in addition, the self-test had good psychometric properties.
The study has shown that the tool has a high initial usage and a low repeated usage. Latent class analysis yielded five distinct classes of users: self-testers, multi-function users, advice users, site visitors, and non-users. Multinomial regression revealed that classes were associated with different risk levels of excessive gambling. The self-testers and multi-function users used the tool to a higher extent and were found to have a greater risk of excessive gambling than the other classes.
Professor Per Carlbring states, “The low usage of the tool is not a disappointment. As long as the right ones actually use the tool, which is exactly what we found. People with a higher risk level are using Playscan more.”
The prevention of problematic gambling is a complex issue. We at Playscan know it all too well. But in order to learn about effective prevention initiatives we use the method of validated learning for acquiring new knowledge.
By practising hypothesis-driven development for responsible gambling we see the development of new tools and services as a series of experiments to determine whether an expected outcome will be achieved – or not. With this we challenge the concept of having fixed requirements when we develop new features. Instead, the process is iterated until we reach a desirable outcome.
6 steps toward hypothesis-driven development
1. We make user research and formulate a hypothesis
Let us look at an example: In interviews with users we often ask them to describe their general attitudes toward their risk assessment. We hear players ask themselves: ok, so this is my risk assessment…but what do I do now?
(This is where we get the chance to identify what the user is expecting from us. From this it is our responsibility to design features that address the problem.)
Our hypothesis is:
We believe that if we clearly communicate the answer to the question “what do I do now?”
Will result in more players reducing their risk level.
We will know we have succeeded when we see an X% increase in risk levels.
2. We define targets and points to measure
We base the work on the products Impact Map, a document that help us drive our software development towards effect, meaning delivering the right responsible gambling initiative to the right player.
Example: X% more risk players know what to do in order to lover their risk level. This is measured with an online questionnaire; click through on recommendations and analysis of the gambling behavior.
3. We design an experiment to test the hypothesis
Best practices and research inspire us when we work on a solution. We talk it through with our experts on problematic gambling, write texts and produce real content.
4. We develop the solution
During the process of making the solution alive software developers, UX-designers and copywriters work closely together. Simply because it always gives us the best result. Then we launch it.
5. We validate the use, accept or reject the hypothesis
This is where we collect feedback from the player and can see if the solution delivers the use we expected. Did it work? Or do we need to change anything? Here we learn and iterate and make it even better.
Our most important work: we iterate!
To ensure that we are on the right course, we work in short iterations that are generally two weeks long. We build the system with small additions of user-valued functionality and evolve by adapting to user feedback. Have we stumbled on any mines? Well of course. But it’s a part of the game – we do not even expect to hit the target at the first time. For every experiment we do we always learn something new. Even if we had a great hypothesis (based on good observations or research) sometimes the results are just neutral. But this is why this method is so effective: we can quickly get a hint on what seems to work – and what’s not working.
A new research study just published in the journal International Gambling Studies showed that at-risk players who received behavioral feedback via Playscan were significantly more likely to reduce the amounts of money they deposited and wagered – compared with players who did not use Playscan.
The authors, Dr Richard Wood and Dr Michael Wohl, conducted the first study of this kind to use actual behavioral data, from 1,558 Internet players in a real-life setting.
“This is a relatively new area of investigation in the responsible gambling field, but our results suggest that such a tool can be very useful to help at-risk players keep better control over their gambling expenditure,” said Dr Richard Wood.
“The study provides empirical evidence, that helping players to better understand their gambling behavior has a sound practical application as a responsible gambling strategy,” added Dr Wohl.
The research provides valuable insight into how a well-designed player-tool, such as Playscan, can be utilized to ensure players have a more responsible gambling experience.
Playscan is thrilled to have been part of the study and to contribute to a better understanding of how to support responsible play.
The latest features from Playscan are now available to players gambling at Miljonlotteriet. The lottery has offered Playscan to their players for more than four years and by upgrading they will now supply players with a new and more detailed view of their gambling behavior.
– What I really like about Playscan 4 is that it is so much more than before, says Ludwig Alholt, CEO at Miljonlotteriet.
– The tool is essential not only for the player, but also for the Operator. It helps us understand and evaluate the impact of our overall responsible gambling initiatives.
Every week Playscan analyzes the gambling habits of 4.5 million players globally. Players appreciate the system, they reflect on their habits, perform self-tests and value the fact that it warns them if their gambling behavior changes into becoming more of a risky one. Which means they remain as a healthy player, as well as in control of their gambling habits.
Miljonlotteriet was founded 1964 and is one of the oldest lotteries in Sweden. We offer scratchcards via subscription, online and with retailers and bingo online. Our vision is to be the operator that is known for creating dreams and making reality out of them. Miljonlotteriet is owned by IOGT-NTO and together we have a dream that no one should have to grow up in a world surrounded by addiction. Since 2000, we have contributed with 1,6 million Swedish kroner to the work of IOGT-NTO. Do you want to know more? Please visit: www.miljonlotteriet.se
We use the Playscan Risk Analysis for two purposes. The original purpose is to use it as a basis for interventions and communication to at-risk players – now, we equally use it together with operators and creators of RG. By looking at levels of risk and changes herein, between groups, marketing campaigns, interventions, etc. we measure the effect of what we do. We quantify, instantaneously and at scale, our mistakes and our successes – every day and for everything we do.
Now, we know that these tools and methodologies could be put to more use out in the world.
Therefore, we’ve added an offering to our product portfolio: the standalone Playscan Risk Analysis. If you already have an RG communication platform or already established RG tools that fits your needs and strategy, and instead is looking to add RG metrics to your operations, this is what you’re looking for.
More-so: if you are not yet ready to invest in an integrated, fully-operational system: we at Playscan now offer our Risk Analysis and methodology as a service called Sustainable Gambling Management.
As the basis of it all, you will get a risk scoring for each of your players. From this seed, a multitude of knowledge sprouts:
Measure the effect of new RG efforts
When you’re launching a new initiative, you’d like to know what effect is has – both to understand the business and RG impact. By bringing in Playscan at the early stage of the project, we will help you track and quantify the results, and measure the effect of your new initiative.
Responsible Gambling KPI:s
The Playscan Risk Analysis unfolds nicely into a set of KPI:s. As an initial step, you may want to try out our metrics by looking at previous years of operation, to get a feeling both our metrics and how they benefit your operation today. When you decide to have these as recurring KPI:s, you have a head start of getting an Analysis Engine installation.
Development of your RG portfolio
If you feel like you’ve added all the tools and information you possibly could, but would like to make the most of it, Playscan AB can help you find a fruitful direction and get some early victories off the ground. We will join forces between your strategies and tools, and our day-to-day experience in reaching the at-risk player.
Reaching the right players with your RG tools
On our three-color-scale (green for low risk, yellow for at-risk, and red for high-risk), we see a big difference between green and yellow players. While the latter is not a uniform group of people, they tend to share traits and behavior that relieves us from much of the fear of annoying or even accusing the low risk players. After all, the green majority of players are those for whom the industry should focus on for a good and exciting experience.
In contrast, the yellow players are slightly different. They tend to identify as players, and gambling is a considerable part of their past-time. They often have self-imposed strategies to keep control of their gambling, and while they may never have developed severe problems from their gambling, they can relate to how it can spin out of control.
Now, the difference between green and yellow is vast: not just in terms of the operator walking the balance between business goals and compliance, but also as a divider between those who (yet, at least) don’t need and don’t want to dig deep into the plethora of tools, and those for whom it is both interesting and relevant.
We know how to communicate with increased risk players: let’s set up a strategy, reaching the right player with the right tool at the right time.
To learn more, pop us an email , catch us at one of the events we’re at or shoot us a tweet!
Phd student David Forsström presenting results from his studies at SNSUS conference and at the Department of Psychology, Stockholm University.
In the first study (to be presented at Stockholm University) user behavior was analyzed and the main finding was the identification of five distinct classes of users: Very high usage, high usage, advice users, site visitors and non-users.
The second study (to be presented at SNSUS) focuses on how the user experiences Playscan. The main findings are that users want more feed-back from the system and that the type of gambling activity online influences Playscan usage.
First study will be presented at Stockholm University at June 2, 2015
The second study will be presented at the SNSUS conference in Stockholm at June 3, 2015
To make sure you have impact, do quick experiments and redesign things based on usability principles. By doing so, we found out that displaying only one recommendation at the time makes more people click.
A click on a recommendation is a success for Playscan. It means that we’ve provoked a reaction or created interest for taking action.
Sometimes, the little stuff create a big difference. As Thaler and Sunstein writes in their bestseller Nudge: “[S]mall and apparently insignificant details can have major impacts on people’s behaviour. A good rule of thumb is to assume that “everything matters””. With the “everything matters” mindset, the insignificant details can indeed prove fruitful beyond expectation.
Back in the days, Playscan always showed two recommendations to players. The rationale was that this was a trade-off between making sure to give the player more than one choice, to make sure he could find something relevant, but not to overwhelm him with too many. From nothing but our own curiosity, we decided to test whether we were correct.
We randomly divided our visitors into three groups, presenting them with one, two or three recommendations respectively. Next, we measured the click-through rate during a two week period. At the end of it, we realized that we had left a good many clicks on the table.
Our original design with two recommendations proved a 20% click-through, measured as the proportion of players who clicked any tip. The three-tip version showed no significant difference, but our one-tip version did: 36% of players clicked the recommendation. Again: the only change was one vs two recommendations – no other design changes, the same selection of recommendation, no new content – and from this we doubled our click-through!
Hindsight is always 20/20, and there is a reasonable explanation for what we found: players are more likely to click through with fewer conflicting and maybe confusing recommendations to choose from. Still, before our test we thought we had an equally good theory of why two recommendations was the way to do things.
So while doubling our click-through on recommendations based only on simplifying things was a big lesson learned, the biggest was without a doubt that “everything matters”. Ideas and hypotheses are a good starting point, but until proven they are just that: hypotheses.
Now, getting people to use our tools is only a first step in having impact. When it comes to recommendations, the next is having relevant ones. How do we make sure that they are? Well, we will test that too.
We tend to talk a lot about consumer protection in the gaming industry. It has become a vital part, and a bit of a buzz in business since a number of online markets have matured and regulatory bodies are challenging the industry into more preventive online actions against problematic gambling.
Therefore there is an urgent need to understand players’ online behavior. Not only for creating a perfect gaming experience: but in the case of consumer protection. But yet, there is still no consistency in what consumer protection really means and the question of “how we protect vulnerable players” has still not been answered. And meanwhile as we discuss all off this, we seem to miss the target.
The information every player provides to us could give us the answer. This article will argue that if we actually value consumer protection, not only as an abstract concept that we nod at agreeably during meetings – we should make use of information available: player data that is understood from a risk perspective.
Identification of high risk gambling in player data
A lot of data is being generated every minute of the day when players gamble both online and within land-based facilities like Casinos or eGaming machines. Purposely designed behavioral tracking solutions can identify patterns of play in gambling data, and with current technology, combined with understandings of problematic gambling; this can be utilized for proactive consumer protection.
Many players, with real life problem gambling stories, express that they have experienced “an escalation of their behavior” and before they knew what was happening: they were placing increased bets, and losing more and more money. By identifying these risk factors in player data – Operators get a new dimension in “knowing your customer”.
Player data holds a lot of information, such as age, gender, favorite game etc. But player data also holds descriptions of a player’s behavior. Looking at data from a risk perspective means to identify possible negative behaviors or risk factors, such as;
Start playing more often
For longer sessions
Constantly changing planned spending limits
These are a few examples that relate to user behavior rather than user information. With a risk analysis, it is possible to make players aware of changes in actual behavior.
This information provides direction for effective responsible gambling initiatives at an early stage, preventing problematic gambling instead of treating a problematic gambler. The risk analysis helps segment the player population into “low risk”, “increased risk” or “high risk” – leaving Operators with information for unique opportunities like customized responsible gambling communications.
How to understand data
Even if we have spent time on data analyses and even when players with risky gambling behavior are identified – it’s still tricky to answer the question “how can we protect vulnerable players?”
Data describes what players do, how they behave. But not really what they need.
One way to understand it and knowing what to do with data is to humanize and bring these numbers to life. For example: Wilma is a 45-year-old woman who likes gambling, especially online bingo. For the past six months she has gambled at a high-risk level, with few gambling-free days. Late nights with bingo, long sessions with lottery tickets after lottery tickets. She finds herself in a loop of wagering more and continuing to gamble, with higher stakes, even after she just lost.
This was not an ideal situation for Wilma, simply because she couldn’t afford it and lately her risk data indicates that she is trying to cut down on her gambling. For example, she is setting strict limits for her gambling that she has managed to keep within.
Should the Operator take any actions? Well, since Wilma previously has been on a high-risk journey, one thing that she does not need is to receive promotions, bonuses and commercials from her gaming company. This is were the operator can differentiate an out-going customer to one that just wants to control their gambling habits.
With customized communications, it could also be wise to inform Wilma, close to play, if her gambling sessions seem to be escalating again.
Why is this all meaningful?
By rethinking the way Operators use data and understand players, they can create meaningful communications that influence and engage the players. By taking the player’s risk level into consideration when communicating with player Operators can better focus on the user’s needs.
Knowing the player’s risk level is valuable through the whole chain of the gambling industry: from game design, marketing and user experience to management and business development all the way to customer support – and the player.
Simply, through understanding risk we avoid “one-size fits all” solutions and then we add true value to the concept of consumer protection. Because the point is that the answer to “how can we protect vulnerable players?” is that it varies according to each player’s risk behavior.
The Norwegian state owned lottery Norsk Tipping has now upgraded the responsible gambling tool Playscan into its latest version: Playscan 4.2. And they are making it mandatory for all their players. Not far after, Svenska Spel, the Swedish state owned lottery, made the same decision.
Players want responsible gambling tools that are easy to use and integrated in their overall gambling experience. That was the starting point for both Norsk Tipping and Svenska Spel.
Bjørn Helge Hoffmann, Chief Adviser Responsible Gaming at Norsk Tipping explains:
– By upgrading to Playscan 4 we are focused to make Playscan into a service for all, i.e. making Playscan mandatory to all our players. With this, our players are offered integrated communications in regards to changes in their gambling habits as part of their overall gaming experience.
Zenita Strandänger, CSR Manager at Svenska Spel, says that it is important for Svenska Spel to assist their players into making informed and responsible decisions about their gambling. She says:
– The tool promotes responsible gambling behaviors and it plays an important role in our overall consumer protection strategy. Making Playscan to a service for all players is simply a natural next step for us.
– We are very happy that these two Operators now is communicating with all their players that are showing signs of increased risk. That is great news for players and for our continued efforts in consumer protection, says Andreas Holmström, CEO of Playscan AB.
What a gambling operator should do when implementing responsible gambling
01.Educate all employees about the importance of responsible gambling. That means all the way from executives to your customer service team. Probably the most important thing to do to get acceptance for responsible gambling.
02. Train and educate retailers about the importance of responsible gambling. Retailers meet players all day long. Don’t underestimate their impact on your overall responsible gambling operations.
03. Get behavioural insights. Use your gambling data to understand the risk level of your customer. And intervene at the right time to minimize risk of harm and to secure sustainable revenue.
04. Customize communication to players needs. Take a critical look at how your gambling site is designed: present your tools and write your responsible gambling information in a way so your players can easily find and use them.
05. Talking about being a responsible gaming provider doesn’t make you one. It requires commitment and actions.
What do you know about your online player? With anonymous players, customer data is an important factor when making strategic business decisions with limited information. However, big data often becomes a faceless collection of information, rather than a true picture of the players’ wants and needs. One still needs to know how to interpret data and how to combine it with other sources of information.
User Personas brings together big data with qualitative user research such as interviews, field studies and observations to gain an overall picture of a user, their needs, goals and motivation. It also fills the gap between what players claim to act upon compared to their measured actions, which in the context of gambling often differs. Combined with big data, User Personas give the answers to three important questions: what are the main target groups, which target groups should be focused on to make the most impact, and how should communications be designed towards those target groups?
User research shows that players are concerned about keeping their gambling under control. An important aid for that is to let the player know how much time and money he or she spends on gambling. Playscan’s new feature will help players keep track of their spending by presenting charts on actual consumption of time and money.
Players can view their results, time spent, and monetary transactions on gambling and directly see patterns and trends. This allows them to get an aggregated view of their habits, and the opportunity to make informed choices about their gambling.
The feature is integrated into Playscan but can also be placed outside of the Playscan interface, as an add-on.
– Transparency is the absolute foundation in responsible gambling. Players ask for this information time and again, and it is our obligation to answer. I am pleased to have this feature in Playscan, and I’m thrilled for the positive response we’ve had from operators, says Henrik Hallberg, CTO Playscan AB.